Response to Reviewer

Methodological Concerns

The reliance on a single 24-hour dietary recall in Phase 1 is insufficient to accurately capture participants' habitual fiber intake. A validated Food Frequency Questionnaire (FFQ) should be implemented during this initial screening phase to mitigate recall bias. Additionally, while the targeted difference in fiber intake between groups was reduced to 15g, the sample size calculation remains unadjusted for this potentially smaller effect size.

Response:

We thank the reviewer for these valuable methodological suggestions. We acknowledge that a single 24-hour dietary recall may not fully capture habitual dietary intake at the individual level. However, in Phase 1 the primary objective is screening and estimating general dietary patterns among a large sample of participants rather than assessing precise long-term nutrient intake. A single 24-hour dietary recall is widely used in epidemiological screening studies to estimate mean group intake when collected from a sufficiently large and heterogeneous population; therefore, it was considered appropriate for the initial screening phase involving approximately 500 participants. To strengthen dietary assessment in the intervention phase, the protocol has been modified so that in Phase 2 dietary intake will be assessed using multiple 24-hour dietary recalls at follow-up time points along with a Food Frequency Questionnaire (FFQ) to better capture habitual intake patterns. Nutrient intake will be analyzed using DietCal software based on standardized Indian food composition tables, which will further improve the reliability of dietary assessment while maintaining feasibility during the large screening phase. In addition, we appreciate the reviewer’s observation regarding the targeted difference in dietary fiber intake between groups being reduced to 15 g/day. The sample size calculation for Phase 2 was not based on the absolute difference in fiber intake but on the expected effect on the primary clinical outcomes, specifically insulin resistance (HOMA-IR) and body mass index (BMI). The power calculation used anticipated standard deviation values derived from previously published intervention studies and the clinically meaningful difference expected for BMI and insulin resistance. Because the calculation was based on changes in these metabolic outcomes rather than fiber intake itself, the reduction in the planned fiber difference from 20 g/day to 15 g/day does not alter the expected clinically meaningful effect on the primary endpoints; therefore, the required sample size remains appropriate and unchanged.

Intervention and Adherence

The active dietary counseling required to reach the 40g daily fiber target makes any claim of blinding impossible, rendering the study an open-label trial. Furthermore, expecting participants to maintain such a high fiber intake from whole foods over six months introduces a severe risk of non-compliance and dropout. The intervention also fails to control for the varying ratios of soluble to insoluble fiber inherent in whole foods, which risks confounding the metabolic outcomes.

Response:

We thank the reviewer for these important observations. We agree that complete blinding is not feasible in dietary behavioral interventions that involve active counseling and individualized dietary guidance; therefore, the study should be considered an open-label randomized controlled trial. This approach is common in nutrition intervention research where participants are required to actively modify their dietary behavior. To minimize potential bias, randomization and allocation concealment will be implemented using stratified block randomization and opaque sealed envelopes. In addition, the primary outcomes are objective measures, including biochemical parameters such as fasting glucose, HbA1c, serum insulin, lipid profile, and body composition analysis, which helps reduce measurement bias despite the open-label design.

We also acknowledge that maintaining a dietary fiber intake of approximately 40 g/day over six months may pose adherence challenges and could potentially increase the risk of non-compliance or dropout. To enhance participant adherence and minimize attrition, several strategies have been incorporated into the protocol, including individualized dietary counseling, customized high-fiber diet charts based on locally available foods, regular telephonic follow-up, dietary tracking sheets, fiber intake compliance checklists, and continuous motivation and reinforcement during follow-up visits. These strategies are widely used in dietary intervention studies and are expected to support sustained compliance throughout the intervention period.

Regarding the concern about varying ratios of soluble and insoluble fiber in whole foods potentially confounding metabolic outcomes, we acknowledge that whole foods naturally contain different proportions of fiber types. However, the primary objective of the study is to evaluate the effect of increasing total dietary fiber intake from whole foods under real-world dietary conditions rather than isolating specific fiber fractions. This approach improves the ecological validity and practical applicability of the findings. Furthermore, dietary intake will be assessed using 24-hour dietary recalls and a Food Frequency Questionnaire (FFQ), which allows estimation of total dietary fiber intake and helps account for dietary variability. Collectively, this design enables the study to evaluate the metabolic effects of increasing total dietary fiber intake within a realistic dietary context.

Manuscript Formatting Issues

The manuscript title contains a prominent typographical error, referring to the study as a "randomized controlled trail" rather than a "trial". The introduction lacks logical flow, occasionally relies on outdated terminology, and inappropriately uses bullet points instead of cohesive academic paragraphs in key sections. A thorough structural revision and professional proofread are necessary to elevate the manuscript to scientific publication standards.

Response:

We thank the reviewer for carefully identifying these formatting and structural issues. The typographical error in the manuscript title has been corrected from “randomized controlled trail” to “randomized controlled trial.” In addition, the Introduction section has been thoroughly revised to improve the logical flow and coherence of the background information. Outdated terminology has been updated where appropriate, and bullet points previously used in narrative sections have been replaced with structured academic paragraphs to maintain consistency with scientific writing standards. Furthermore, the entire manuscript has undergone careful proofreading and structural revision to enhance clarity, readability, and overall presentation in accordance with journal publication standards.

Lack of Justification for a Single-Sex Study:

The original protocol failed to adequately explain why the study is restricted exclusively to middle-aged women. While the authors later cited menopause and estrogen-related metabolic changes in their response, this fundamental rationale was missing from the protocol's background.

Response:

We thank the reviewer for highlighting this important point. We acknowledge that the initial protocol did not sufficiently explain the rationale for restricting the study to middle-aged women, and this has now been clarified in the revised background section. Middle-aged women represent a population at increased risk of metabolic disorders due to hormonal changes associated with the menopausal transition. During this period, declining estrogen levels are associated with increased visceral adiposity, alterations in body composition, and reduced insulin sensitivity, all of which contribute to a higher risk of overweight, obesity, and metabolic disturbances. These physiological and metabolic changes make middle-aged women a particularly relevant population for examining the potential benefits of dietary interventions such as increased dietary fiber intake on insulin resistance and body composition. Accordingly, the revised manuscript now clearly states this sex-specific rationale in the background section to justify the focus on middle-aged women.

Missed Opportunity for a Crossover Design:

The authors did not consider a crossover design. In dietary studies where blinding is impossible and inter-individual variability is high, having participants act as their own controls (by switching between the 25g and 40g diets) could have significantly strengthened the evidence.

Response:

We acknowledge that crossover designs can reduce inter-individual variability in dietary studies by allowing participants to serve as their own controls. However, a crossover design was not considered appropriate for the present study due to several practical and methodological considerations. First, the intervention period in this study is relatively long (6 months), and implementing a crossover design would require an additional intervention phase along with an adequate washout period to minimize carryover effects, which would substantially extend the total study duration. Second, repeated switching between dietary patterns (from 25 g to 40 g fiber intake and vice versa) may be challenging for participants and could negatively influence adherence to the prescribed diet. Therefore, a parallel randomized controlled trial design was considered more feasible and appropriate for evaluating the long-term effects of increased dietary fiber intake in this population.

Vague Secondary Objectives:

The secondary objective, stated simply as "To assess the opinions of women on modified fiber intake," was heavily criticized for being too vague and lacking specific, measurable parameters.

Response:

Thank you for your valuable comment. It was operationalized using a structured, dichotomous (yes/no) questionnaire administered at predefined time points (30th, 90th, and 180th day). Each item captured specific, measurable aspects of participant opinion, including acceptance of modified fiber intake, perceived ease of implementation, and willingness to continue the dietary changes. The use of binary responses ensured quantifiability, while repeated assessments enabled longitudinal tracking of changes in opinion and compliance over time.

Missing Justification for Variables:

The authors plugged specific numbers into their power calculation (like standard deviations of 3.96 for BMI and 5.06 for insulin resistance) but initially failed to justify where these specific estimates came from or why they represented a "clinically significant difference".

Response:

We thank the reviewer for highlighting the need to justify the parameters used in the sample size calculation. In the revised manuscript, we have clarified the source and rationale for the values used in the power calculation. The estimates for the standard deviation (σ) of BMI (3.96) and insulin resistance (5.06) were derived from previously published intervention studies examining the effects of dietary or lifestyle interventions on metabolic outcomes in similar adult populations. These values were selected as they represent realistic variability observed in comparable studies. The minimum detectable difference (d) was chosen based on changes considered clinically meaningful in the context of improvements in BMI and insulin resistance following dietary interventions. Thus, the parameters used in the sample size calculation were selected to ensure adequate statistical power to detect clinically relevant changes in the primary outcomes. These details and supporting references have now been added to the Methods section to improve transparency and clarity of the sample size estimation.

Unproven Feasibility of the Intervention:

Increasing a patient's dietary fiber by an additional 15g to 20g per day exclusively through whole foods is notoriously difficult. Reviewers questioned whether the research team had any pilot data proving they could successfully achieve and sustain this massive leap in fiber intake over 6 months.

Response:

We thank the reviewer for raising this important concern regarding the feasibility of achieving and sustaining an increased dietary fiber intake through whole foods. Prior to initiating the intervention, preliminary observations from our earlier dietary assessment conducted among middle-aged women in the same clinical setting indicated that many participants were consuming substantially lower amounts of dietary fiber than recommended levels. Therefore, the intervention was designed to increase fiber intake gradually through locally available, culturally acceptable high fiber foods such as whole grains, legumes, fruits, and vegetables, rather than relying on fiber supplements. In addition, participants in the intervention group receive individualized dietary counseling, a customized high fiber diet plan, and regular follow-up reinforcement through telephonic monitoring, which are intended to facilitate adherence and support gradual dietary modification over time. These strategies were incorporated to improve the feasibility and sustainability of achieving the targeted fiber intake.

No Objective Compliance Biomarkers:

Despite the known flaws of self-reported dietary recalls and food frequency questionnaires, the study lacks any objective physiological markers to prove participants actually ate the fiber (such as stool weight, transit time, or specific microbiome metabolite markers). Adding a "compliance checklist" does not solve the fundamental issue of subjective reporting.

Response:

We thank the reviewer for this important observation. We agree that objective biomarkers can strengthen the assessment of dietary compliance in nutrition intervention studies. However, the inclusion of objective biomarkers such as stool analysis (e.g., stool weight, transit time, or microbial metabolites) or other microbiome-related markers was not feasible in the present study. During the planning phase, the possibility of incorporating stool analysis was considered; however, participants expressed reluctance and practical concerns regarding stool sample collection, which posed challenges for participant acceptance and compliance in a community-based dietary intervention study. Additionally, logistical and resource constraints limited the feasibility of conducting microbiome or metabolite analysis. Furthermore, the absence of objective biomarkers such as stool analysis has now been acknowledged as a limitation in the manuscript.

Confusing Protocol Structure:

Reviewers found the methodology highly confusing because Phase 1 (the screening phase) and Phase 2 (the randomized trial) were jumbled together without clear separation or a concise timeline.

Response:

Thank you for this observation. In response, Phase 1 (screening phase) and Phase 2 (randomized controlled trial) have now been clearly delineated and described as distinct components of the study. This separation was initially clarified in Version 1 of the revised manuscript, and the same structured presentation has been consistently maintained and further refined in subsequent versions. Additionally, the methodology section has been reorganized to improve clarity, with a more explicit description of the study flow and timeline for each phase to avoid any overlap or confusion.

Reduce redundancy in the introduction and discussion to improve readability and maintain focus.

Background

Obesity is a major public health concern worldwide. Urbanization, economic growth, changing lifestyles, and dietary habits have contributed to a “double burden” of diseases in rapidly developing low- and middle-income countries such as India¹. The average dietary fiber intake is below the recommended levels, and the World Health Organization estimates that the incidence of obesity has increased globally in the past decade. Many individuals do not consume adequate fiber to meet recommended intakes, and obese women often report lower dietary fiber consumption compared with normal-weight individuals. ²

Dietary fiber plays an important role in appetite regulation and weight management. Fiber-rich foods promote satiety and reduce hunger by delaying gastric emptying and increasing stomach fullness.³ These effects are particularly evident among individuals with obesity.⁴ In addition, dietary fiber consumption promotes the growth of beneficial bacteria in the colon, which may help prevent obesity, metabolic syndrome, and adverse intestinal changes.⁵

High-fiber diets are associated with improved health outcomes and a reduced risk of several chronic diseases. Fiber-rich foods typically have lower energy density and can replace high-fat, energy-dense foods in the diet. Increased dietary fiber intake has been linked with improvements in serum lipoproteins, blood pressure, blood glucose control, and body weight. Individuals consuming adequate fiber are at lower risk of coronary artery disease, stroke, hypertension, diabetes, obesity, and gastrointestinal disorders. In addition, soluble fiber intake has been shown to enhance immune function. ⁶

Dietary fiber obtained from fruits, vegetables, legumes, and whole grains provides several physiological benefits and is associated with a lower risk of chronic diseases such as cardiovascular disease, type 2 diabetes mellitus, obesity, and certain cancers. These foods also provide micronutrients and phytochemicals that contribute to overall health, highlighting the importance of promoting adequate dietary fiber intake in the population.⁷

However, limited research has examined the role of dietary fiber specifically in the treatment and management of obesity, and further studies are required to strengthen the evidence linking dietary fiber intake with obesity-related outcomes.⁸ Dietary fiber also promotes the growth of beneficial gut bacteria and supports microbial balance. Increased consumption of dietary fiber and whole grains enhances the growth of beneficial intestinal microbiota, which may be particularly relevant in individuals with obesity and other metabolic disorders. However, these effects may vary depending on the type, structure, and composition of the fiber and whole-grain sources.⁹

High-fiber foods are more satiating and contribute to appetite control by influencing gastric emptying, reducing food intake, and promoting a sense of fullness.¹⁰ Fermentation of dietary fiber in the colon produces short-chain fatty acids that regulate appetite through gut hormones such as cholecystokinin and glucagon-like peptides, which help reduce hunger and increase satiety.¹¹ Increased chewing and gastric distension associated with fiber-rich foods may further enhance satiety and regulate food intake.¹²

This study focuses on weight reduction through increased dietary fiber consumption. According to the Indian Council of Medical Research and National Institute of Nutrition guidelines, the recommended dietary fiber intake is 40 g per 2000 kcal of energy intake.¹³ Increasing dietary fiber consumption to recommended levels may support weight management and improve overall metabolic health.

Discussion

Evidence on the association between dietary fiber intake and metabolic outcomes among overweight and obese middle-aged women in India remains limited. This study aimed to examine whether increased dietary fiber intake can improve insulin resistance, body composition, and weight in this population. Dietary fiber provides several metabolic benefits, including enhanced satiety, improved glycemic control, reduced cholesterol levels, and increased fat oxidation. By lowering energy intake and supporting metabolic regulation, adequate fiber consumption may contribute to effective weight management. In addition to dietary intervention, participants in the intervention group received regular dietary counseling, which may have improved adherence to the recommended dietary practices and encouraged healthier lifestyle behaviors. Therefore, the observed improvements in metabolic indicators and body composition may reflect the combined influence of increased dietary fiber intake and the supportive role of counseling in promoting sustained dietary and behavioral changes.

Present the sample size calculation formula in a clearer and more legible format, ensuring that readers can easily follow the computation steps.

Sample Size Calculation

The sample size was calculated using the following formula:

n=(2(Z_(1-α/2)+Z_(1-β) )^2 σ^2 [1+(m-1)ρ])/(md^2 )

Where:

            n = sample size per group

            Z₁₋α/₂ = 1.96 (for α = 0.05, two-tailed test)

            Z₁₋β = 0.84 (for 80% statistical power)

            σ = anticipated population standard deviation of the outcome variable

            d = clinically significant difference (effect size)

            m = number of time points/follow-ups (m = 2)

            ρ = intraclass correlation coefficient (ρ = 0.4)

Computation for BMI

Parameters used:

            σ = 3.96

            d = 1.5

            m = 2

            ρ = 0.4

Step 1: Substitute values into the formula

n=(2(1.96+0.84)^2 (3.96)^2 [1+(2-1)×0.4])/(2(1.5)^2 )

Step 2: Simplify

n=(2(2.8)^2 (15.68)(1.4))/(2(2.25))

Step 3: Final estimate

n≈77" participants per group"

Adjustment for 15% dropout rate:

n=77/(1-0.15)=90

Therefore, 90 participants per group were required.

Computation for Insulin Resistance

Parameters used:

            σ = 5.06

            d = 2

            m = 2

            ρ = 0.4

Step 1: Substitute values

n=(2(1.96+0.84)^2 (5.06)^2 [1+(2-1)×0.4])/(2(2)^2 )

Step 2: Simplify

n=(2(2.8)^2 (25.60)(1.4))/(2(4))

Step 3: Final estimate

n≈71" participants per group"

Adjustment for 15% dropout rate:

n=71/(1-0.15)=83

Thus, 83 participants per group were required.

Include a detailed adherence analysis plan, such as a checklist or monitoring tool to assess actual fiber consumption and compliance with the dietary recommendations.

Women with no contraindications to high dietary fiber consumption and abnormal HOMA-IR will be included in Phase 2 of the study. Baseline assessments will be conducted for both intervention and control groups. Demographic information including age, religion, place of residence, type of family, number of family members, marital status, education, occupation, and income will be collected using a structured proforma. Anthropometric measurements such as height (stadiometer), body weight (weighing scale), and waist and hip circumference will be recorded in the outpatient department. Biochemical parameters including fasting blood glucose (hexokinase method), HbA1c (TINA method), serum insulin (ECLIA), and lipid profile (triglycerides GPO Trinder method, HDL direct homogeneous method, LDL enzymatic method, and total cholesterol CE-CHOD-POD method) will be assessed. Dietary intake will be assessed using a 24-hour dietary recall and a Food Frequency Questionnaire (FFQ), and nutrient intake will be analyzed using DietCal software version 6.3. Adherence to dietary fiber intervention will be monitored using multiple strategies, including a tracking sheet to record daily intake of fiber-rich foods and a fiber intake compliance checklist during follow-up visits. Monthly telephonic follow-ups will be conducted to reinforce dietary counseling, evaluate adherence to the recommended dietary practices, and address any challenges faced by participants. Participants’ feedback on high-fiber food consumption will also be documented to identify adherence patterns and potential barriers, ensuring systematic monitoring of dietary fiber intake and compliance with the intervention throughout the study period. Physical activity levels will be assessed using the Global Physical Activity Questionnaire (GPAQ), and body composition parameters including visceral fat, subcutaneous fat, and muscle mass will be measured using a body fat analyzer. Clinical assessment will also be performed to document physical complaints reported by participants.

Consider incorporating measures of gut microbiota, since the study rationale emphasizes the role of fiber in modulating intestinal bacteria and metabolic health

Although dietary fiber is known to influence metabolic health through modulation of gut microbiota, gut microbial composition was not assessed in this study, which primarily focused on clinical and metabolic outcomes such as insulin resistance, body composition, and weight. Future studies incorporating microbiome analysis may provide better insight into the mechanisms linking dietary fiber intake with metabolic health

Response for F1000

The second secondary objective is not specific enough. Opinion on what?

In phase 1 I doubt whether a single 24 hour recall is adequate to determine usual intake. I wonder whether a food frequency questionnaire designed for measuring fiber intake would be more suitable. Is there evidence to support that a single 24 hour recall gives a sufficiently accurate estimate of usual intake of fiber?

To minimize potential bias, participants reporting atypical or irregular dietary patterns were excluded, thereby ensuring that the recorded dietary recall reasonably reflected usual intake.

We recognize that a more detailed dietary assessment is essential for evaluating individual-level nutrient adequacy, particularly dietary fiber intake. Accordingly, in the subsequent intervention phase, we plan to implement a structured high-fiber dietary intervention combined with supportive physical activity. Dietary intake will be assessed using three non-consecutive 24-hour recalls along with a validated Food Frequency Questionnaire (FFQ) to capture habitual intake patterns more comprehensively. Physical activity will be assessed using the Global Physical Activity Questionnaire (GPAQ). This integrated approach will enable a more robust assessment of habitual diet while facilitating the evaluation of changes in insulin sensitivity and related metabolic outcomes.

Are 500 participants in phase 1 enough to provide 180 participants who agree to being randomized in phase 2? This is not explained clearly.

In Phase 1, a total of 500 overweight and obese middle-aged women will be screened to determine the prevalence of insulin resistance using HOMA-IR . Based on existing epidemiological evidence and our preliminary observational study conducted among 564 women, a high prevalence of insulin resistance is anticipated in this population. In the preliminary study, over 55% of participants were obese and approximately 20% were overweight, yielding an observed obese-to-overweight ratio of approximately 2:1 .

Taking this distribution into account, along with the expected prevalence of insulin resistance and potential exclusions and non-participation in the intervention phase, a screening sample of 500 participants was considered adequate to ensure the recruitment of 180 eligible and consenting participants for Phase 2 . This approach allows for appropriate representation of both overweight and obese groups in the randomized phase while maintaining sufficient statistical power for the intervention analyses.

It is not clear to me what is meant by “The sample size was calculated in accordance with insulin resistance and BMI.” Please give more details on the sample size calculation. What input was used? What sample size calculation method

Published intervention studies examining the effects of dietary fiber on insulin resistance and BMI were used as reference sources to determine realistic and clinically meaningful estimates of the expected standard deviation (s) and the minimum detectable difference (d) for these outcomes (references 34 and 35).

Phase 2:

The information on the sample size calculation is not complete: two essential parameters for the sample size calculations are s = anticipated population standard deviation of the outcome variable and d = clinically significant difference. The authors do not provide the values they used for these parameters, nor do they justify why the choice for this d and s was made. The sample size formula given cannot be correct and is also not formatted correctly (s2 instead of s2).

I understand the difference in fiber intake between control and treatment groups was changed from 20 g/day to 15 g/day in this new version of the protocol. However, the sample size did not change, while I would expect that a higher sample size would be needed as the effect (d) would be lower with a smaller difference.

For instance, the role of the microbiome is mentioned, interspersed with statements on other aspects, giving the introduction a repetitive character. Another example is the second sentence where a statement on fiber and an unrelated statement on obesity are combined into a single sentence without the sentence making clear why they are combined.

Similarly, there is the sentence “There are few studies on the utilization of dietary fiber in the treatment of obesity, but further research is required to confirm stronger associations between dietary fiber and obesity”, where “but” implies a contradiction between the first and the second part, while I don’t see the contradiction.

Parts of the protocol are not written out but only given in bullet points. I found this both strange for a paper, and also often unclear.  For instance, under strength an limitations: “Good knowledge and practice regarding modified diet plans with high dietary fiber will be addressed to participants”. Knowledge of whom? Of the researcher or the participants? How will this knowledge be addresses?  

Response: Strengths and limitations: The study is expected to demonstrate improvements in insulin resistance, body composition, and body weight among participants with higher dietary fiber intake. Participants will receive structured guidance on modified high-fiber diet plans, which is intended to improve their knowledge and dietary practices, as well as to identify barriers and challenges related to sustained fiber consumption. Potential limitations include participant dropout due to dietary non-compliance, variability in long-term adherence to the prescribed diet, and limited generalizability due to hospital-based recruitment and resource constraints.

1. Clarity in Methods Section (Phase 1 & Phase 2 Separation)

Phase 1

Objective

The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.

Study Setting

This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.

Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.

Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.

Phase 2: Randomized Controlled Trial (RCT)

Objective

To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.

Study Design

Randomized, controlled trial.

Intervention group

All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be ass. Necessaryessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.

Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).

CONTROL ARM

Day 1

Traditional/standard care

(patient will be called to OPD)

Day 15

Nil

Day 30

Nil

Day 60

Nil

Day 90

(patient will be called to OPD)

Basic data:

Tool 2: 24hr recall and food frequency

Tool 3: GPAQ

Biochemical parameters:

FBS, HbA1c, Sr. Insulin and lipid profile

Body fat analyzer:

Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention

(patient will be called to OPD)

Customize the individual-specific diet plan

Nutritional counseling

Impart nutritional empowerment on fiber consumption

Handover of diet plan

Day 15

Reinforcement

(through telephone)

Tool 2: 24hr recall

Tool 3: GPAQ

Modification of diet plan (if required)

Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall

Tool 3: GPAQ

Modification of diet plan (if required)

Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall

Tool 3: GPAQ

Modification of diet plan (if required)

Motivate to adhere to the intervention

Day 90

Outcome assessment

(patient will be called to OPD)

Basic data:

Tool 2: 24-hour recall and food frequency

Tool 3: GPAQ

Tool 4: Clinical assessment scale

Tool 5: Patient opinion on a modified diet

Biochemical parameters:

FBS, HbA1c, Sr. Insulin and lipid profile

Body fat analyzer:

Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow a customized diet plan

Day 180

Checking compliance

(patient will be called to OPD)

Basic data:

Tool 2: 24-hour recall and food frequency

Tool 3: GPAQ

Tool 4: Clinical assessment scale

Tool 5: Compliance checklist

Biochemical parameters:

FBS, HbA1c, Sr. Insulin and lipid profile

Body fat analyzer:

Visceral fat, S/C fat, muscle mass

Day 135

Nil

Day180

(patient will be called to OPD)

Basic data:

Tool 2: 24hr recall and food frequency

Tool 3: GPAQ

Biochemical parameters:

FBS, HbA1c, Sr. Insulin and lipid profile

Body fat analyser:

Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study

This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.  

López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.

4. Updating Scientific Terminology in the Background Section

We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.

5. Clarification on Double-Blinding and Study Design

There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an essential role in the analysis.

6. Sample Size Discrepancy

The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration

The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration

The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.

The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns

Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)

The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that proportions soluble and insoluble fiber appropriately. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.

. Clarity in Methods Section (Phase 1 & Phase 2 Separation)

Phase 1

Objective

The primary aim of Phase 1 is to screen middle-aged overweight and obese women to determine the prevalence of insulin resistance.

Study Setting

This phase will be conducted in the Outpatient Departments (OPDs) of Medicine, Gynaecology, and Endocrinology at Kasturba Hospital, Manipal.

Sample Size & Selection

A total of 500 women will be screened to assess insulin resistance.

Participants will undergo a baseline assessment, including:

Demographic Information: Age, education, occupation, income, marital history, place of residence, and family structure.

Phase 2: Randomized Controlled Trial (RCT)

Objective

To assess the impact of high dietary fiber intake (40g/day) on insulin resistance, body composition, and weight among overweight and obese women.

Study Design

Randomized, controlled trial.

Intervention group

All women in the intervention arm will be counseled for about 15 minutes, and a customized diet chart consisting of high fiber of 40 grams will be provided. Nutritional empowerment on fiber shall be delivered to each woman enrolled. Necessary dietary advice on the modified diet plan and with a motivation to adhere to the diet plan will be communicated only to the intervention group. After the first counselling, on the 15th day, women will be telephonically assessed on their 24-hour recall dietary intake. On the 30th day, the women will be contacted telephonically again to record their 24-hour recall of their dietary intake. Necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 60th day, the women will be again telephonically contacted to record their 24-hour recall on their dietary intake, and necessary dietary changes on the modified diet plan will be advised, and motivation to adhere to the diet plan will be continued. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat is analyzed using body fat analyzer and a questionnaire on patient opinion regarding modified diet plan shall be assessed as motivation and adherence towards fiber consumption subjects will be communicated telephonically on the 135th day. From the 136th to the 180th day, there shall not be any conversation regarding dietary modifications. On the 180th day, as a compliance-checking, the women will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data .24hr dietary recall, food frequency analyzed using DietCal version 6.3., physical activity data assessed by using GPAQ, body fat analyzed using body fat analyzer and diet compliance on the modified diet plan shall be assessed.

Control group.

Women in the control arm will get a traditional diet care plan with 25gm of fiber according to their health condition. Necessary dietary advice will be communicated to the control group on the first visit to the hospital. There shall be no telephonic communication with the control group till the 90th day. On the 90th day, as an outcome-based assessment, women will be called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hour dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer. On the 180th day, as a compliance-checking, the patient will be again called to the hospital for the anthropometric data, biochemical data followed by dietary data, a 24-hr dietary recall, food frequency analyzed using DietCal version 6.3, physical activity data assessed by using GPAQ, and body fat is analyzed using body fat analyzer

Data Analysis

Repeated Measures ANOVA will be used to evaluate changes in insulin resistance, body composition, and weight over time.

Ethical Considerations

Approval obtained from the Institutional Research Committee and Institutional Ethics Committee (IEC).

CONTROL ARM

Day 1

Traditional/standard care

(patient will be called to OPD)

Day 15

Nil

Day 30

Nil

Day 60

Nil

Day 90

(patient will be called to OPD)

Basic data:

Tool 2: 24hr recall and food frequency

Tool 3: GPAQ

Biochemical parameters:

FBS, HbA1c, Sr. Insulin and lipid profile

Body fat analyzer:

Visceral fat, S/C fat, muscle mass

INTERVENTION ARM

Day 1

Intervention

(patient will be called to OPD)

Customize the individual-specific diet plan

Nutritional counseling

Impart nutritional empowerment on fiber consumption

Handover of diet plan

Day 15

Reinforcement

(through telephone)

Tool 2: 24hr recall

Tool 3: GPAQ

Modification of diet plan (if required)

Motivate to adhere to the intervention

Day 30

Tool 2: 24hr recall

Tool 3: GPAQ

Modification of diet plan (if required)

Motivate to adhere to the intervention

Day 60

Tool 2: 24hr recall

Tool 3: GPAQ

Modification of diet plan (if required)

Motivate to adhere to the intervention

Day 90

Outcome assessment

(patient will be called to OPD)

Basic data:

Tool 2: 24-hour recall and food frequency

Tool 3: GPAQ

Tool 4: Clinical assessment scale

Tool 5: Patient opinion on a modified diet

Biochemical parameters:

FBS, HbA1c, Sr. Insulin and lipid profile

Body fat analyzer:

Visceral fat, S/C fat, muscle mass

Day 135

Reinforcement (through telephone)

Motivation to follow customised diet plan

Day 180

Checking compliance

(patient will be called to OPD)

Basic data:

Tool 2: 24hr recall and food frequency

Tool 3: GPAQ

Tool 4: Clinical assessment scale

Tool 5: Compliance checklist

Biochemical parameters:

FBS, HbA1c, Sr. Insulin and lipid profile

Body fat analyser:

Visceral fat, S/C fat, muscle mass

Day 135

Nil

Day180

(patient will be called to OPD)

Basic data:

Tool 2: 24hr recall and food frequency

Tool 3: GPAQ

Biochemical parameters:

FBS, HbA1c, Sr. Insulin and lipid profile

Body fat analyser:

Visceral fat, S/C fat, muscle mass

3. Rationale for Sex-Specific Differences and Justification for a Single-Sex Study

This study is specifically designed for women’s health, as obesity and insulin resistance present distinct physiological and hormonal influences in females. The decision to focus on middle-aged women was based on prior evidence suggesting unique metabolic responses to dietary interventions in this demographic.  

López, M. et al. (2016) - "Menopause, obesity, and insulin resistance: An emerging paradigm"

This study specifically explores the impact of menopause on metabolic health, highlighting the increased risk of insulin resistance and obesity in women as they transition through menopause. It aligns with your focus on middle-aged women and the unique metabolic responses they experience.

4. Updating Scientific Terminology in the Background Section

We appreciate the suggestion regarding outdated terminology. The term "roughage" and other obsolete language will be revised to align with current scientific terminology.

5. Clarification on Double-Blinding and Study Design

There was an error in the original study design description. This study is not a double-blind study but rather an open-ended study. This design was chosen to facilitate a deeper understanding of the real-world effects of dietary interventions on obesity and insulin resistance in middle-aged women, where factors like adherence to the intervention and participant feedback play an important role in the analysis.

6. Sample Size Discrepancy

The final sample size of 180 participants (90 per group) was determined based on power calculations for insulin resistance and BMI, accounting for a 15% dropout rate. To ensure appropriate representation, participants were stratified based on the prevalence of obesity and overweight, maintaining a 2:1 ratio, with a higher proportion of obese individuals, as obesity is more prevalent in the target population.

7. Clarification of Study Duration

The total duration of the intervention is 180 days (6 months) for the intervention group, with structured follow-ups to ensure adherence and assess outcomes. Participants receive customized dietary counseling on Day 1, followed by reinforcement sessions via telephone on Days 15, 30, and 60 to monitor compliance and provide necessary modifications. Outcome assessments are conducted on Day 90 and Day 180, where anthropometric, biochemical, and dietary data are collected. A motivational follow-up is done on Day 135 to encourage continued adherence. The control group follows the same assessment schedule but does not receive interim dietary modifications. This structured timeline ensures a comprehensive evaluation of the intervention’s impact while maintaining participant engagement.

8. Justification for the 20g Fiber Difference and Study Duration

The 20g difference in fiber intake between groups was selected based on existing dietary recommendations and evidence supporting its impact on weight management and metabolic health. The intervention group receives 40g of fiber per 2000 kcal, aligning with the Indian Council of Medical Research (ICMR) and National Institute of Nutrition (NIN) guidelines. In contrast, the control group follows a standard 25g fiber intake. This difference ensures a meaningful contrast while remaining practical for adherence.

The 180-day (6-month) intervention period was chosen to allow sufficient time for stabilizing dietary habits and for metabolic changes, such as improvements in insulin resistance and body composition, to be observed. The feasibility of increasing dietary fiber intake by 20g has been supported by our preliminary observational study (2019), which assessed fiber intake and obesity among 564 women. This study highlighted a significant negative correlation between fiber intake and BMI, reinforcing the need for a structured dietary intervention to promote increased fiber consumption.

9. Addressing Compliance Assessment Concerns

Compliance assessment in this study is not solely based on 24-hour dietary recall; multiple tools are incorporated to ensure accuracy and reliability. In addition to the 24-hour recall and food frequency questionnaire, a compliance checklist is used to track adherence to the prescribed dietary plan. Furthermore, patient opinions on the modified diet are collected to assess acceptability and feasibility. Regular reinforcement sessions (via telephone on Days 15, 30, and 60) further help monitor compliance and address challenges.

10. Consistency in Fiber Composition (Soluble vs. Insoluble)

The study ensures consistency in dietary fiber composition across participants by providing a structured, customized diet plan that appropriately proportions soluble and insoluble fiber. The dietary sources primarily include whole grains, legumes, vegetables, and fruits, providing a balanced fiber mix. While the metabolic effects of soluble and insoluble fiber can vary, the intervention is designed to reflect a realistic, well-balanced dietary intake, aligning with established dietary guidelines. This approach ensures that all participants receive a comparable fiber composition, minimizing variability in metabolic responses while maintaining dietary feasibility.